Automatic cataract grading methods based on deep learning.

Journal: Computer methods and programs in biomedicine
Published Date: Aug 5, 2019

Abstract

BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and effective treatment. We develop an algorithm and platform to automatically diagnose and grade cataract based on fundus images of patients. This method can help government assisting poor population more accurately.

Authors

  • Hongyan Zhang
    Beijing Tongren Eye Center, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and visual Sciences, National Engineering Research Center for Ophthalmology, Beijing, China.
  • Kai Niu
    Key Laboratory of Universal Wireless Communations, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Yanmin Xiong
    Key Laboratory of Universal Wireless Communations, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Weihua Yang
    Shenzhen Eye Institute, Shenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong Province, China.
  • ZhiQiang He
    Key Laboratory of Universal Wireless Communations, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China; College of Big Data and Information Engineering, Guizhou University, Guizhou, China. Electronic address: hezq@bupt.edu.cn.
  • Hongxin Song
    Beijing Tongren Eye Center, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and visual Sciences, National Engineering Research Center for Ophthalmology, Beijing, China. Electronic address: songhongxin2012@163.com.

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